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license: apache-2.0 |
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tags: |
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- summarisation |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-old |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-old |
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This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6733 |
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- Rouge1: 60.9431 |
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- Rouge2: 49.8688 |
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- Rougel: 42.4663 |
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- Rougelsum: 59.836 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 0.8246 | 1.0 | 223 | 0.6974 | 55.2742 | 41.9883 | 37.8584 | 53.7602 | |
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| 0.6396 | 2.0 | 446 | 0.6786 | 56.0006 | 43.1917 | 38.5125 | 54.4571 | |
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| 0.5582 | 3.0 | 669 | 0.6720 | 57.8912 | 45.7807 | 40.0807 | 56.4985 | |
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| 0.505 | 4.0 | 892 | 0.6659 | 59.6611 | 48.0095 | 41.752 | 58.5059 | |
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| 0.4611 | 5.0 | 1115 | 0.6706 | 59.7241 | 48.164 | 41.4523 | 58.5295 | |
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| 0.4254 | 6.0 | 1338 | 0.6711 | 59.8524 | 48.1821 | 41.2299 | 58.6072 | |
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| 0.3967 | 7.0 | 1561 | 0.6718 | 60.3009 | 49.0085 | 42.0306 | 59.0723 | |
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| 0.38 | 8.0 | 1784 | 0.6733 | 60.9431 | 49.8688 | 42.4663 | 59.836 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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